environment_setup.txt

For This Video Streaming Solution have used Ubuntu 22.04 as Host OS & used webcam for verification.
Note : It is recommended to check this solution on GPU enabled system as we are using Yolo based AI inference for object detection
which requires GPU for better performance.

Environment Setup : 
a) Install packages like ffmpeg.
b) Install Anaconda to create Virtual Environment so that it does not affect the main system environment.
   Link : 
	https://docs.anaconda.com/anaconda/install/#manual-shell-init-linux

   Follow the installation instructions mentioned in the link to install and configure anaconda.
   I have considered Linux (Ubuntu 22.04) as my host environment. You can install version as per your Host OS.

   Steps to Create & Configure Virtual Environment :
   Open a Terminal & Enter below commands -
   1) source ~/anaconda3/bin/activate (This path may vary based on the installation path selected for anaconda)
   2) conda create --name <name_of_env> python=3.11 (It will ask to install some package, select y)
   3) conda activate <name_of_env>
   4) mkdir -p ~/projects && cd ~/projects
   5) git clone https://github.com/avp24/Video-Streaming-Solution.git
   6) cd video_streaming_solution
   7) pip install -r requirements.txt
   8) pip install ultralytics (This command will take some time as it will be installing all the packages w.r.t yolov8 for Class Detections 
      on Camera Stream)
   9) pip install websockets

Note : Environment Creation steps have to be executed once. After Virtual Environment configuration whenever a new terminal is opened enter commands -
--> source ~/anaconda3/bin/activate
--> conda activate <name_of_env> (Can use conda env list to check if multiple environments are created) 
Execute Application :
1) cd ~/projects/video_streaming_solution
2) python main.py
It will start the script and http server will start on port 8088
3) Open browser and navigate to <ip_address>:8088 or 127.0.0.1:8088.
You should be able to see Live Stream with Object Detection enabled.